An epitome of an image is a condensed representation containing the essence of the textural and structure properties of the image. The epitome approach aims at reducing redundant information (texture) in the image by exploiting repeated content within the image.
It is known to factor an image into a texture epitome E and a transform map φ. The epitome principle was first disclosed by Wang et al. in the article entitled “Factoring Repeated Content Within and Among Images” published in the proceedings of ACM SIGGRAPH 2008 (ACM Transaction on Graphics, vol. 27, no. 3, pp. 1-10, 2008). FIG. 1 illustrates the method of Hoppe. From an image Y, a texture epitome E and a transform map φ are determined such that all image blocks of Y can be reconstructed from matched patches of E. A matched patch is also known as transformed patch. As opposed to blocks, the patches belong to a pixel grid. Once the self-similarities are determined in the image Y, the method of Hoppe determines redundant texture patches to construct epitome charts, the union of all epitome charts constituting the texture epitome E. Each epitome chart represents repeated regions in the image. The construction of an epitome chart is composed of a chart initialization step followed by several chart extension steps. The transform map φ is an assignation map that keeps track of the correspondences between each block of the image Y and a texture patch of the texture epitome E. The transform map is also known as vector map or assignment map in the literature. With the texture epitome E and the transform map φ, one is able to reconstruct an image Y′ whose content is very similar to the content of the image Y. In the following the epitome designates both the texture epitome E and the transform map φ.
In European patent application EP2011794733, a method to construct an epitome is disclosed that comprises finding self-similarities among the image and then determines redundant texture patches to construct epitome charts. Specifically, finding self-similarities comprises for each block Bi in the image Y, determining a set of patches in the same image with similar content, i.e. that approximates Bi with a given error tolerance ε. Such a solution is time consuming and memory demanding.